A multiobjective memetic algorithm with particle swarm optimization and Q-learning-based local search for energy-efficient distributed heterogeneous hybrid flow-shop scheduling problem

Expert Systems with Applications, Год журнала: 2023, Номер 237, С. 121570 - 121570

Опубликована: Сен. 20, 2023

Язык: Английский

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Mathematical model and knowledge-based iterated greedy algorithm for distributed assembly hybrid flow shop scheduling problem with dual-resource constraints

Expert Systems with Applications, Год журнала: 2023, Номер 239, С. 122434 - 122434

Опубликована: Ноя. 4, 2023

Язык: Английский

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A tri-individual iterated greedy algorithm for the distributed hybrid flow shop with blocking

Expert Systems with Applications, Год журнала: 2023, Номер 237, С. 121667 - 121667

Опубликована: Сен. 20, 2023

Язык: Английский

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The application of heterogeneous graph neural network and deep reinforcement learning in hybrid flow shop scheduling problem

Computers & Industrial Engineering, Год журнала: 2023, Номер 187, С. 109802 - 109802

Опубликована: Дек. 1, 2023

Язык: Английский

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An iterated greedy algorithm with acceleration of job allocation probability for distributed heterogeneous permutation flowshop scheduling problem

Swarm and Evolutionary Computation, Год журнала: 2024, Номер 88, С. 101580 - 101580

Опубликована: Май 3, 2024

Язык: Английский

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A Q-learning driven multi-objective evolutionary algorithm for worker fatigue dual-resource-constrained distributed hybrid flow shop

Computers & Operations Research, Год журнала: 2024, Номер unknown, С. 106919 - 106919

Опубликована: Ноя. 1, 2024

Язык: Английский

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Q-learning-based multi-objective particle swarm optimization with local search within factories for energy-efficient distributed flow-shop scheduling problem

Journal of Intelligent Manufacturing, Год журнала: 2023, Номер unknown

Опубликована: Окт. 25, 2023

Язык: Английский

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A Q-learning-driven genetic algorithm for the distributed hybrid flow shop group scheduling problem with delivery time windows

Information Sciences, Год журнала: 2025, Номер unknown, С. 121971 - 121971

Опубликована: Фев. 1, 2025

Язык: Английский

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A Deep Reinforcement Learning-Based Evolutionary Algorithm for Distributed Heterogeneous Green Hybrid Flowshop Scheduling

Processes, Год журнала: 2025, Номер 13(3), С. 728 - 728

Опубликована: Март 3, 2025

Due to increasing energy consumption, green scheduling in the manufacturing industry has attracted great attention. In distributed involving heterogeneous plants, accounting for complex work sequences and consumption poses a major challenge. To address hybrid flowshop (DHGHFSP) while optimising total weighted delay (TWD) (TEC), deep reinforcement learning-based evolutionary algorithm (DRLBEA) is proposed this article. DRLBEA, problem-based heuristic initialization with random-sized population designed generate desirable initial solution. A bi-population global search local used obtain elite archive. Moreover, distributional Deep Q-Network (DQN) trained select best strategy. Experimental results on 20 instances show 9.8% increase HV mean value 35.6% IGD over state-of-the-art method. The effectiveness efficiency of DRLBEA solving DHGHFSP.

Язык: Английский

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Q-learning based estimation of distribution algorithm for scheduling distributed heterogeneous flexible flow-shop with mixed buffering limitation

Engineering Applications of Artificial Intelligence, Год журнала: 2025, Номер 149, С. 110537 - 110537

Опубликована: Март 12, 2025

Язык: Английский

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